The rapid growth of semiconductor and display manufacturing highlights the demand for fast, precise motion stages. Advanced systems such as lithography and bio-stages require accuracy at the μm and nm levels, but linear motor stages face challenges from disturbances, model uncertainties, and measurement noise. Disturbances and uncertainties cause deviations from models, while noise limits control gains and performance. Disturbance Observers (DOBs) enhance performance by compensating for these effects using input–output data and a nominal inverse model. However, widening the disturbance estimation bandwidth increases noise sensitivity. Conversely, the Kalman Filter (KF) estimates system states from noisy measurements, reducing noise in position feedback, but it does not treat disturbances as states, limiting compensation. To address this, we propose an Augmented Kalman Filter (AKF)–based position control for linear motor stages. The system was modeled and identified through frequency response analysis, and DOB and AKF were implemented with a PIV servo filter. Experimental validation showed reduced following error, jitter, and control effort, demonstrating the improved control performance of the AKF approach over conventional methods.

Centrifugal compressor is a device that converts kinetic energy to increase the air pressure. It rotates at a high speed of up to 200,000 RPM and directly affects aerodynamic noise. Various studies have already been conducted, but the direct calculation method of acoustics based on the unsteady solution is inefficient because it requires a lot of resources and time. Therefore, flow characteristics and numerical comparison according to various aerodynamic factors predicted as a cause of noise generation were analyzed in this study based on the steady solution. High-frequency noise was calculated locally near the asymmetric flow properties. Vortex and turbulent kinetic energy were generated at similar locations. Among static components, a large-sized vortex of 3.48×10⁷ s^-1 was distributed at the location where the rotational flow around the compressor wheel combined with the inlet suction flow. In addition, a locally high vortex of 8.16×10⁵ s^-1 was distributed around the balancing cutting configurations that cause asymmetric flow characteristics. Analysis of these factors and causes that directly affect noise can be efficiently improved in the pre-design stage. Therefore, the efficient design methodology for centrifugal compressors that considers both performance and noise is expected based on the results of this study.

This study introduces a highway secondary accident prevention system that employs Fast Fourier Transform (FFT) analysis of vehicle collision sounds. The system is designed to identify abnormal acoustic patterns produced during collisions and skidding events, enabling faster and more accurate accident detection than traditional methods. When a crash is detected, visual warning signals are instantly sent to nearby vehicles using LED devices powered by a photovoltaic panel and an energy storage system (ESS). Experimental results showed 100% detection accuracy during independent playback of collision, skidding, and driving sounds, and 80% accuracy during simultaneous playback. These results confirm the system's ability to effectively differentiate accident-related sounds and deliver timely alerts. This research offers an innovative and environmentally sustainable approach to enhancing highway safety and reducing the societal and economic consequences of secondary accidents.